Historic and Modern Approaches for the Discovery of Abandoned Wells for Methane Emissions Mitigation in Oil Creek State Park, Pennsylvania.

Hundreds of oil wells were drilled along Oil Creek in Pennsylvania in the mid-1800s, birthing the modern oil industry. No longer in operation, many wells are now classified as abandoned, and, due to their age, their locations are either unknown or inaccurately recorded. These historic-well sites present environmental, safety, and economic concerns in the form of possible methane leaks and physical hazards. Airborne magnetic and LiDAR surveys were conducted in the Pioneer Run watershed in Oil Creek State Park to find abandoned wells in a historically significant but physically challenging location. Wells were drilled in this area prior to modern geolocation and legal documentation. Although a large number of old wells were abandoned summarily without remediation of the site, much of the land area within Oil Creek State Park is now covered in trees and dense underbrush, which can obscure wellheads. The thick vegetation and steep terrain limited the possibility of ground-based surveys to easily find well sites for methane emissions studies. The data from remote sensing surveys were used to corroborate potential well locations from historic maps and photographs. Potential well sites were verified in a ground-based field survey and monitored for methane emissions. Two historic photographs documenting oil activity in the late 1800s were georeferenced using a combination of magnetic and LiDAR data. LiDAR data, which were more useful in georeferencing and in field verification, identified 290 field locations in the Pioneer Run watershed, 86% of which were possible well sites. Sixty-two percent of the ground-verified wells remained unplugged and comprised the majority of leaking wells. The mean methane emissions factor for unplugged wells was 0.027 ± 0.099 kg/day, lower than other Appalachian Basin methane emissions estimates. LiDAR was used for the first time, in combination with an airborne magnetic survey, to reveal underground oil industry features and inform well identification and remediation efforts in difficult-to-navigate regions. In the oldest oil fields, where well casing has been removed or wood conductor casing was installed, historic photographs provide additional lines of evidence for oil wells where ground disturbances have concealed surface features. Identification of well sites is necessary for mitigation efforts, as unplugged wells emit methane, a potent greenhouse gas.

Historic and modern approaches for discovery of abandoned wells for methane emissions mitigation in Oil Creek State Park, Pennsylvania.

BACKGROUND: Hundreds of oil wells were drilled along Oil Creek in Pennsylvania in the mid-1800s, birthing the modern oil industry. No longer in operation, many wells are now classified as abandoned, and, due to their age, their locations are either unknown or inaccurately recorded. These historic well sites present environmental, safety, and economic concerns in the form of possible methane leaks and physical hazards. METHODS: Airborne magnetic and LiDAR surveys were conducted in the Pioneer Run watershed in Oil Creek State Park to find abandoned wells in a historically significant but physically challenging location. Wells were drilled in this area prior to modern geolocation and legal documentation. Although a large number of old wells were abandoned summarily without remediation of the site, much of the land area within Oil Creek State Park is now covered in trees and dense underbrush, which can obscure wellheads. The thick vegetation and steep terrain limited the possibility of ground-based surveys to easily find well sites for methane emissions studies. The data from remote sensing surveys were used to corroborate potential well locations from historic maps and photographs. Potential well sites were verified in a ground-based field survey and monitored for methane emissions. RESULTS: Two historic photographs documenting oil activity in the late 1800s were georeferenced using a combination of magnetic and LiDAR data. LiDAR data, which were more useful in georeferencing and in field verification, identified 290 field locations in the Pioneer Run watershed, 86% of which were possible well sites. Sixty-two percent of the ground-verified wells remained unplugged and comprised the majority of leaking wells. The mean methane emissions factor for unplugged wells was 0.027 ± 0.099 kg/day, lower than other Appalachian Basin methane emissions estimates. CONCLUSIONS: LiDAR was used for the first time, in combination with an airborne magnetic survey, to reveal underground oil industry features and inform well identification and remediation efforts in difficult-to-navigate regions. In the oldest oil fields, where well casing has been removed or wood conductor casing was installed, historic photographs provide additional lines of evidence for oil wells where ground disturbances have concealed surface features. Identification of well sites is necessary for mitigation efforts, as unplugged wells emit methane, a potent greenhouse gas.

Constraining natural gas pipeline emissions in San Juan Basin using mobile sampling.

Quantifying methane (CH4) leaks of pipeline systems is critical to ensure accurate emission factors in regional and global atmospheric models. The previous emission factors in the United States Environmental Protection Agency (EPA) Greenhouse Gas Inventory (GHGI) are from 1996 and do not reflect the modern gathering pipeline system. Additional data from different basins across the United States are urgently needed to improve the emission factors. The National Energy Technology Laboratory conducted a ground-based vehicle survey at Carson National Forest in the San Juan Basin, New Mexico, in September 2019. 187 km of natural gas gathering pipeline systems were surveyed. The mobile CH4 survey system was efficient in identifying CH4 plumes and pinpointing the leak sources. Gaussian dispersion modeling suggested our survey system had a minimum detection limit of 1.5 LPM. No leaks were found from the pipelines while a leak of 7.1 +/- 0.2 LPM was on a pig launcher door and another leak of 0.7 +/- 0.1 LPM on a block valve. Limited access to the gathering pipeline system prevented us from quantifying all potential leaks detected by the CH4 sensors. The low leak frequency phenomenon was also observed in the sole existing study of natural gas gathering pipelines in the Fayetteville Shale.

Identifying Abandoned Well Sites Using Database Records and Aeromagnetic Surveys.

Oil and natural gas are primary sources of energy in the United States. Improved drilling and extracting techniques have led to a renewed interest in historic oil and gas fields, but limited records of legacy wells make new drilling efforts more difficult, as abandoned wells may provide conduits for liquids and gases to migrate into groundwater reservoirs or the atmosphere. Well finding using aeromagnetic surveys pinpoints the location of steel-cased wells, detecting both active and abandoned wells, including buried casings lacking aboveground markers. Here, we present six aeromagnetic surveys conducted in Pennsylvania and Wyoming as case studies, comparing the magnetic points to locations known in databases. In all study sites, more magnetic points were detected than recorded in databases. Based on differences between theoretical database well counts and the actual number of wells detected in surveys, we estimated the total number of wells in Pennsylvania to be 395 000-466 000 and 181 000-182 000 in Wyoming. Extrapolating to the national level, we estimate the average number of wells in the continental United States is 6.04 ± 19.97 million wells with 1.16 ± 3.84 million of those designated as abandoned wells, within the range of previous abandoned well count estimations. Although aeromagnetic surveys are limited to detecting steel-cased wells and do not differentiate sites based on well status, this study nevertheless demonstrates the utility of aeromagnetic surveys in well finding efforts across the country and shows limitations in database records of oil and natural gas wells.

Quantifying source contributions of volatile organic compounds under hydraulic fracking moratorium.

Volatile organic compounds (VOCs) are precursors for ozone (O3) and secondary particulate matter, which contribute to asthma and cardiovascular diseases. With the technology development of hydraulic fracking, the United States experienced a shale gas boom in the last decade while the public raised concerns about the potential health impacts of co-emitted VOCs and other airborne pollutants. National Energy Technology Laboratory conducted stationary trailer-based ambient monitoring to study the sources of VOCs in Maryland, where the state enacted a moratorium on unconventional natural gas extraction. The campaign had two periods, May to August 2014 (summer) and November 2014 to February 2015 (winter). Ethane was the most abundant VOC, averaging 12.3 ppb (SD = 15.7 ppb) in summer and 21.7 ppb (SD = 21.6 ppb) in winter. The seasonal variation of VOCs indicated different source strengths. The sampling region was in the nitrogen oxides (NOx) limited regime for O3 production, and the O3 concentrations were sensitive to VOC/NOx ratios in the early mornings. We derived a six-factor profile using positive matrix factorization: motor vehicles, industrial, biogenics, coal burning, fugitive and evaporative, and ozone secondary. The fugitive and evaporative factor explained 44.5% of total VOCs, and the motor vehicles factor followed second with 15.5%. Oil and gas activities had a considerable impact on the abundance of VOCs in this region.

Beyond-the-Meter: Unaccounted Sources of Methane Emissions in the Natural Gas Distribution Sector.

The United States Environmental Protection Agency maintains an inventory of greenhouse gas emissions in accordance with the Intergovernmental Panel on Climate Change. Methane (CH4), a potent gas with a global warming potential 86-125× that of carbon dioxide (CO2) over a twenty-year period, is the main component of natural gas (NG). As NG becomes an increasingly larger percentage of the energy resources used in the United States, it is ever more important to evaluate the CH4 emissions inventory. However, the inventory also does not account for all possible sources of CH4 leaks, contributing to uncertainty in the national CH4 inventory. Discrepancies between top-down and bottom-up inventories of CH4 emissions imply that there are significant unaccounted-for sources of CH4 leaks, especially over cities. Diffuse CH4 plumes above cities that are not attributable to distribution pipelines or other NG infrastructure suggest many small beyond-the-meter leaks together contribute to large emissions. Here, we evaluate the distribution sector of the CH4 emissions inventory and make suggestions to improve the inventory by analyzing end-user emissions. Preliminary research into beyond-the-meter emissions suggests that while individually small, the appliances and buildings that make up the residential sector could contribute significantly to national scale emissions. Furnaces are the most leak-prone of appliances, contributing to 0.14% of total CH4 emissions from the NG sector in the United States. Combining measurements from whole house emissions and steady-state operation of appliances, we estimate that residential homes and appliances could release 9.1 Gg CH4 yearly in the United States, totaling over 2% of the CH4 released from the NG sector. While factors such as appliance age and usage, climate, and residential setting could influence the emissions profile of individual appliances, these preliminary estimates justify further exploration of beyond-the-meter emissions.

Atmospheric impacts of a natural gas development within the urban context of Morgantown, West Virginia.

The Marcellus Shale Energy and Environment Laboratory (MSEEL) in West Virginia provides a unique opportunity in the field of unconventional energy research. By studying near-surface atmospheric chemistry over several phases of a hydraulic fracturing event, the project will help evaluate the impact of current practices, as well as new techniques and mitigation technologies. A total of 10 mobile surveys covering a distance of approximately 1500 km were conducted through Morgantown. Our surveying technique involved using a vehicle-mounted Los Gatos Research gas analyzer to provide geo-located measurements of methane (CH4) and carbon dioxide (CO2). The ratios of super-ambient concentrations of CO2 and CH4 were used to separate well-pad emissions from the natural background concentrations over the various stages of well-pad development, as well as for comparisons to other urban sources of CH4. We found that regional background methane concentrations were elevated in all surveys, with a mean concentration of 2.699 ± 0.006 ppmv, which simply reflected the complexity of this riverine urban location. Emissions at the site were the greatest during the flow-back phase, with an estimated CH4 volume output of 20.62 ± 7.07 g/s, which was significantly higher than other identified urban emitters. Our study was able to successfully identify and quantify MSEEL emissions within this complex urban environment.

Measurement of atmospheric pollutants associated with oil and natural gas exploration and production activity in Pennsylvania's Allegheny National Forest.

Oil and natural gas exploration and production (E&P) activities generate emissions from diesel engines, compressor stations, condensate tanks, leaks and venting of natural gas, construction of well pads, and well access roads that can negatively impact air quality on both local and regional scales. A mobile, autonomous air quality monitoring laboratory was constructed to collect measurements of ambient concentrations of pollutants associated with oil and natural gas E&P activities. This air-monitoring laboratory was deployed to the Allegheny National Forest (ANF) in northwestern Pennsylvania for a campaign that resulted in the collection of approximately 7 months of data split between three monitoring locations between July 2010 and June 2011. The three monitoring locations were the Kane Experimental Forest (KEF) area in Elk County, which is downwind of the Sackett oilfield; the Bradford Ranger Station (BRS) in McKean County, which is downwind of a large area of historic oil and gas productivity; and the U.S. Forest Service Hearts Content campground (HC) in Warren County, which is in an area relatively unimpacted by oil and gas development and which therefore yielded background pollutant concentrations in the ANF. Concentrations of criteria pollutants ozone and NO2 did not vary significantly from site to site; averages were below National Ambient Air Quality Standards. Concentrations of volatile organic compounds (VOCs) associated with oil and natural gas (ethane, propane, butane, pentane) were highly correlated. Applying the conditional probability function (CPF) to the ethane data yielded most probable directions of the sources that were coincident with known location of existing wells and activity. Differences between the two impacted and one background site were difficult to discern, suggesting the that the monitoring laboratory was a great enough distance downwind of active areas to allow for sufficient dispersion with background air such that the localized plumes were not detected. Implications: Monitoring of pollutants associated with oil and natural gas exploration and production activity at three sites within the Allegheny National Forest (ANF) showed only slight site-to-site differences even with one site far removed from these activities. However, the impact was evident not in detection of localized plumes but in regional elevated ethane concentrations, as ethane can be considered a tracer species for oil and natural gas activity. The data presented serve as baseline conditions for evaluation of impacts from future development of Marcellus or Utica shale gas reserves.

Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis.

Fine particulate matter (PM2.5) concentrations associated with 202 24-hr samples collected at the National Energy Technology Laboratory (NETL) particulate matter (PM) characterization site in south Pittsburgh from October 1999 through September 2001 were used to apportion PM2.5 into primary and secondary contributions using Positive Matrix Factorization (PMF2). Input included the concentrations of PM2.5 mass determined with a Federal Reference Method (FRM) sampler, semi-volatile PM2.5 organic material, elemental carbon (EC), and trace element components of PM2.5. A total of 11 factors were identified. The results of potential source contributions function (PSCF) analysis using PMF2 factors and HYSPLIT-calculated back-trajectories were used to identify those factors associated with specific meteorological transport conditions. The 11 factors were identified as being associated with emissions from various specific regions and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. Three sources associated with transport from coal-fired power plants to the southeast, a combination of point sources to the northwest, and a steel mill and associated sources to the west were identified. In addition, two secondary-material-dominated sources were identified, one was associated with secondary products of local emissions and one was dominated by secondary ammonium sulfate transported to the NETL site from the west and southwest. Of these 11 factors, the four largest contributors to PM2.5 were the secondary transported material (dominated by ammonium sulfate) (47%), local secondary material (19%), diesel combustion emissions (10%), and gasoline combustion emissions (8%). The other seven factors accounted for the remaining 16% of the PM2.5 mass. The findings are consistent with the major source of PM2.5 in the Pittsburgh area being dominated by ammonium sulfate from distant transport and so decoupled from local activity emitting organic pollutants in the metropolitan area. In contrast, the major local secondary sources are dominated by organic material.

Apportionment of ambient primary and secondary fine particulate matter during a 2001 summer intensive study at the CMU Supersite and NETL Pittsburgh site.

Gaseous and particulate pollutant concentrations associated with five samples per day collected during a July 2001 summer intensive study at the Pittsburgh Carnegie Mellon University (CMU) Supersite were used to apportion fine particulate matter (PM2.5) into primary and secondary contributions using PMF2. Input to the PMF2 analysis included the concentrations of PM2.5 nonvolatile and semivolatile organic material, elemental carbon (EC), ammonium sulfate, trace element components, gas-phase organic material, and NO(x), NO2, and O3 concentrations. A total of 10 factors were identified. These factors are associated with emissions from various sources and facilities including crustal material, gasoline combustion, diesel combustion, and three nearby sources high in trace metals. In addition, four secondary sources were identified, three of which were associated with secondary products of local emissions and were dominated by organic material and one of which was dominated by secondary ammonium sulfate transported to the CMU site from the west and southwest. The three largest contributors to PM2.5 were secondary transported material (dominated by ammonium sulfate) from the west and southwest (49%), secondary material formed during midday photochemical processes (24%), and gasoline combustion emissions (11%). The other seven sources accounted for the remaining 16% of the PM2.5. Results obtained at the CMU site were comparable to results previously reported at the National Energy Technology Laboratory (NETL), located approximately 18 km south of downtown Pittsburgh. The major contributor at both sites was material transported from the west and southwest. Some difference in nearby sources could be attributed to meteorology as evaluated by HYSPLIT model back-trajectory calculations. These findings are consistent with the majority of the secondary ammonium sulfate in the Pittsburgh area being the result of contributions from distant transport, and thus decoupled from local activity involving organic pollutants in the metropolitan area. In contrast, the major local secondary sources were dominated by organic material.